BRAVO: Multimodal and Multilingual Advanced Answers Search

BRAVO is devoted to research on technologies to improve the answers search in both text and voice, and the main result is a platform for a modular answers search system which allows to measure the improvement of different techniques for questions classification, answer extraction, passages retrieval, etc. SPINDEL is one of the techniques developed in this project, an entity recognizer which, regardless of language, applies machine learning based on bootstrapping. In the framework of BRAVO project, one of the current research areas is related to the location of drug names and interactions between them in the medical literature using UMLS, dictionaries and USAN rules of naming drugs. As a result, it is available automatically annotated corpus using the DrugNer system (developed by the Advances Databases Group) with generic drug names and other biomedical concepts and manually evaluated by a pharmacological expert. The system combines information obtained by the UMLS MetaMap Transfer (MMTx) program and nomenclature rules recommended by the World Health Organization (WHO) International Nonproprietary Names (INNs) Program to identify and classify pharmaceutical substances